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- Publisher Website: 10.1109/TPWRD.2021.3119918
- Scopus: eid_2-s2.0-85117747360
- WOS: WOS:000846890500054
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Article: Improved S-Transform for Time-Frequency Analysis for Power Quality Disturbances
Title | Improved S-Transform for Time-Frequency Analysis for Power Quality Disturbances |
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Authors | |
Keywords | Fourier transform Gaussian window harmonics analysis improved S-transform power quality Time-frequency analysis |
Issue Date | 2022 |
Citation | IEEE Transactions on Power Delivery, 2022, v. 37, n. 4, p. 2942-2952 How to Cite? |
Abstract | Renewable energy sources will be more vigorously deployed under the global trend of carbon emission reduction. The connection of numerous renewable energy sources poses an increasingly critical challenge to power quality (PQ) issues in power systems. Time-frequency analysis (TFA) is a foundational technique for real-time monitoring and disturbance detection for power signals. This paper develops an improved S-transform (IST) to accurately detect the disturbances such as oscillatory transient, time-varying harmonics and interharmonics, flicker, swell, sag, interrupt, phase jump, and frequency variation. The proposed IST features the exploration of a designed Gaussian window as the kernel function, whose shape and frequency spectrum can be controlled using a standard deviation based detection frequency parameter. This ensures that the detection requirements at different detection frequencies can be easily met. The IST can be realized by fast Fourier transform (FFT) and its inverse, which ensures that it can be implemented quickly. The IST can accurately detect the amplitude and phase information of fundamental signal, which is beneficial to determine the start and end time, and the intensity of disturbance. With the increase of detection frequency, IST also has excellent energy concentration performance. Simulation and experimental results validated the effectiveness and feasibility of the proposed method. |
Persistent Identifier | http://hdl.handle.net/10722/336288 |
ISSN | 2021 Impact Factor: 4.825 2020 SCImago Journal Rankings: 1.570 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Liang, Chengbin | - |
dc.contributor.author | Teng, Zhaosheng | - |
dc.contributor.author | Li, Jianmin | - |
dc.contributor.author | Yao, Wenxuan | - |
dc.contributor.author | Wang, Lei | - |
dc.contributor.author | He, Qing | - |
dc.contributor.author | Hu, Shiyan | - |
dc.date.accessioned | 2024-01-15T08:25:14Z | - |
dc.date.available | 2024-01-15T08:25:14Z | - |
dc.date.issued | 2022 | - |
dc.identifier.citation | IEEE Transactions on Power Delivery, 2022, v. 37, n. 4, p. 2942-2952 | - |
dc.identifier.issn | 0885-8977 | - |
dc.identifier.uri | http://hdl.handle.net/10722/336288 | - |
dc.description.abstract | Renewable energy sources will be more vigorously deployed under the global trend of carbon emission reduction. The connection of numerous renewable energy sources poses an increasingly critical challenge to power quality (PQ) issues in power systems. Time-frequency analysis (TFA) is a foundational technique for real-time monitoring and disturbance detection for power signals. This paper develops an improved S-transform (IST) to accurately detect the disturbances such as oscillatory transient, time-varying harmonics and interharmonics, flicker, swell, sag, interrupt, phase jump, and frequency variation. The proposed IST features the exploration of a designed Gaussian window as the kernel function, whose shape and frequency spectrum can be controlled using a standard deviation based detection frequency parameter. This ensures that the detection requirements at different detection frequencies can be easily met. The IST can be realized by fast Fourier transform (FFT) and its inverse, which ensures that it can be implemented quickly. The IST can accurately detect the amplitude and phase information of fundamental signal, which is beneficial to determine the start and end time, and the intensity of disturbance. With the increase of detection frequency, IST also has excellent energy concentration performance. Simulation and experimental results validated the effectiveness and feasibility of the proposed method. | - |
dc.language | eng | - |
dc.relation.ispartof | IEEE Transactions on Power Delivery | - |
dc.subject | Fourier transform | - |
dc.subject | Gaussian window | - |
dc.subject | harmonics analysis | - |
dc.subject | improved S-transform | - |
dc.subject | power quality | - |
dc.subject | Time-frequency analysis | - |
dc.title | Improved S-Transform for Time-Frequency Analysis for Power Quality Disturbances | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/TPWRD.2021.3119918 | - |
dc.identifier.scopus | eid_2-s2.0-85117747360 | - |
dc.identifier.volume | 37 | - |
dc.identifier.issue | 4 | - |
dc.identifier.spage | 2942 | - |
dc.identifier.epage | 2952 | - |
dc.identifier.eissn | 1937-4208 | - |
dc.identifier.isi | WOS:000846890500054 | - |